Multiscale Approach to the Determination of the Photoactive Yellow Protein Signaling State Ensemble

Abstract

The nature of the optical cycle of photoactive yellow protein (PYP) makes its elucidation challenging for both experiment and theory. The long transition times render conventional simulation methods ineffective, and yet the short signaling-state lifetime makes experimental data difficult to obtain and interpret. Here, through an innovative combination of computational methods, a prediction and analysis of the biological signaling state of PYP is presented. Coarse-grained modeling and locally scaled diffusion map are first used to obtain a rough bird's-eye view of the free energy landscape of photo-activated PYP. Then all-atom reconstruction, followed by an enhanced sampling scheme; diffusion map-directed-molecular dynamics are used to focus in on the signaling-state region of configuration space and obtain an ensemble of signaling state structures. To the best of our knowledge, this is the first time an all-atom reconstruction from a coarse grained model has been performed in a relatively unexplored region of molecular configuration space. We compare our signaling state prediction with previous computational and more recent experimental results, and the comparison is favorable, which validates the method presented. This approach provides additional insight to understand the PYP photo cycle, and can be applied to other systems for which more direct methods are impractical.

Picosecond Photobiology: Watching a Signaling Protein Function in Real Time via Time-Resolved Small- and Wide-Angle X-ray Scattering

“…46–48 Using transition path sampling of explicit solvent molecular dynamics simulations on the millisecond time scale, Vreede et al sought to examine conformational changes accompanying the transition to the PYP signaling state. 47 They concluded that formation of the signaling state involves unfolding of α -helical region 43–51, which in turn leads to solvent exposure of both Glu46 and the PCA chromophore.…”

“…The results reported here unveil a structure transition far more dramatic than described by Vreede et al and likely involves unfolding of the 25-residue N-terminal domain. Subsequent efforts to characterize theoretically the signalingstate ensemble via a multiscale approach 48 concluded that their computational results differ from the experimental results reported by Kim et al and stated "More work is needed to understand this aspect of the PYP photo cycle. "…”

Top-down Multiscale Approach To Simulate Peptide Self-Assembly from Monomers

“…Top-down Simulations of Amyloid Peptides Validate the Generality of Our Theory and Approach. For further tests, we simulated the aggregation of three amyloid peptides (27 peptides with a minimum separation of 30 Å between all of the peptides), including the GNNQQNY segment from the yeast prion protein Sup35 (PDBID: 1YJP), the amyloid-β (Aβ (16)(17)(18)(19)(20)(21)(22), PDBID: 2MXU), and the α-synuclein fragment (α-syn , PDBID: 2N0A). We measured the diffusion coefficients of the monomers for GNNQQNY peptide, Aβ (16)(17)(18)(19)(20)(21)(22), and α-syn at different stages in preparation for eq 4 (Figure 2 and Table S5).…”

“…The serial multiscale method carries out modeling at different resolutions in sequence, which takes advantages of sampling efficiency at lower resolutions and detailed accuracy at higher resolutions. It has been applied to problems that are currently difficult to simulate with the AA models. − A straightforward setup of serial simulations includes top-down modeling, which starts from the least detailed model and recovers the details until a fully atomistic model is obtained. However, serial top-down simulations have never been systematically tested with more than two resolutions.…”

Predictive collective variable discovery with deep Bayesian models

“…An additional local scale parameter, indicating the distance around a specific configuration presumably could be well approximated by a low-dimensional hyperplane tangent. LSDMap is applied in [43] and enhances the exploration of the configurational space as shown in [44]. More recent approaches to collective variable discovery work under a common variational approach for conformation dynamics (VAC) 45 and employ a combination of basis functions for defining the eigenfunctions to the backward Fokker-Planck operator.…”